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Publications
  • January 2013
  • Article
  • Journal of Public Economics

Preference Heterogeneity and Optimal Capital Income Taxation

By: Mikhail Golosov, Maxim Troshkin, Aleh Tsyvinski and Matthew Weinzierl
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Abstract

We examine a prominent justification for capital income taxation: goods preferred by those with high ability ought to be taxed. In an environment where commodity taxes are allowed to be nonlinear functions of income and consumption, we derive an analytical expression that reveals the forces determining optimal commodity taxation. We then calibrate the model to evidence on the relationship between skills and preferences and extensively examine the quantitative case for taxes on future consumption (saving). In our baseline case of a unit intertemporal elasticity, optimal capital income tax rates are 2% on average and 4.5% on high earners. We find that the intertemporal elasticity of substitution has a substantial effect on optimal capital taxation. If the intertemporal elasticity is one-third, optimal capital income tax rates rise to 15% on average and 23% on high earners; if the intertemporal elasticity is two, optimal rates fall to 0.6% on average and 1.6% on high earners. Nevertheless, in all cases that we consider, the welfare gains of using optimal capital taxes are small.

Keywords

Taxation

Citation

Golosov, Mikhail, Maxim Troshkin, Aleh Tsyvinski, and Matthew Weinzierl. "Preference Heterogeneity and Optimal Capital Income Taxation." Journal of Public Economics 97 (January 2013): 160–175. (Also NBER Working Paper Series, No. 16619, December 2010.)
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About The Author

Matthew C. Weinzierl

Business, Government and the International Economy
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More from the Authors
  • Made In Space, Expectations Management, and the Business of In-Space Manufacturing By: Matthew C. Weinzierl and Mehak Sarang
  • Designing, Not Checking, for Policy Robustness: An Example with Optimal Taxation By: Benjami Lockwood, Afras Y. Sial and Matthew C. Weinzierl
  • Understanding Different Approaches to Benefit-Based Taxation By: Robert Scherf and Matthew C. Weinzierl
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